Buy or Sell on Hard Hit%

A few days back, David Appelman announced the addition of Hard Hit, Medium Hit and Soft Hit data to the batted ball stats on FanGraphs. Since then, I have been playing around with them, and found some interesting things.

But I had no idea what to make of those things. If a guy has an extremely high Hard Hit%, what does that mean? Should we expect regression? Should we expect it to continue? And what does that mean for fantasy value?

Some very cursory research suggests that the answer depends on whether you are talking about a hitter or a pitcher. A number of us at Rotographs – Alex Chamberlain, Eno Sarris, and myself, to be exact, looked for evidence of whether giving up hard/soft contact or creating hard/soft contact was a skill.

There is more research to be done – particularly looking at stabilization rates within season. But our first look was at year-over-year correlation. Those of you who frequent this data-heavy corner of the nets will know that if something is a skill, we expect to see a high YoY correlation. If pitcher X is really, really good at making guys hit the ball weakly, he should still be good at that the next year and the year after, in general.

But that is not what we see. All of us found very low YoY correlations for pitchers. Specifically, Alex found a correlation of .25 YoY for Hard Hit% using 2002-2014 data.

So what that tells us is that if you see a pitcher generally throwing well (high K%-BB% for example) but with a sky-high HH%, that solid contact is likely not his fault and will regress to the mean.

For example, Joe Kelly of the Red Sox has been piling up Ks and his walks haven’t been too bad. His HH% is 36%, tied for 7th highest in baseball and a significant increase over anything that has happened to him in the past. The implication of the low YoY correlation is that the contact he gives up should get softer in the future, likely leading to fewer hits and better overall numbers.

Hitters, on the other hand, do seem to have a HH skill. Chamberlain found a correlation of .69, again similar to what others found. This tells us something different – namely that a hitter who is smoking the ball is probably going to keep smoking the ball.

Take a look at Ryan Braun. He has a 43.6% HH%, 7th highest in the game.His Hard-Medium-Soft split is very similar to Mike Trouts. Yet he has a .264 BABIP and a good-but-not-Braun-like .248/.327/.436 line. But we have reason to believe he’ll continue to create a lot of hard contact, which means the overall line should improve as well.

At the other end of the spectrum, Sonny Gray has the league’s lowest HH% against and I have to wonder when the other shoe will drop for him. Chase Utley, in the meantime, seems like a buy low candidate, and his BABIP will surely improve, but he is also sandwiched between Everth Cabrera and Ben Revere for the 5th lowest HH%. That suggests a guy who has just lost it, not a guy just waiting to break out.

As I said before, this is just a first step and there is more to come from the team on how to use this data, but this is a start – at least year-to-year, hitting the ball hard is a skill; inducing soft contact is not.

A long-time fantasy baseball veteran and one of the creators of ottoneu, Chad Young's writes for RotoGraphs and PitcherList, and can be heard on the ottobot podcast. You can follow him on Twitter @chadyoung.

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Mike W.
7 years ago

Great article, as a Ryan Braun owner it has helped ease some of my fears that had started to creep in. I got him for a decent price, but knew the injury/age risk was hanging over him. Glad to see as long as he can stay healthy, he should put up better numbers for me going forward.

In regards to Kelly, maybe this is a stupid question, but is it possible that he has changed something mechanically or pitch wise that has allowed him to rack up the K’s, but also made him more prone to being hit harder than earlier in his career? He has never really shown this kind of K potential and it seems his velocity has increased as well. Is it possible that while he pitches may have better movement on them, leading to more K’s that his control has suffered a bit as a result and he is hanging more pitches or something? I know in his last start he got hammered and struggled with Walks.

Jeff Zimmermanmember
7 years ago
Reply to  Mike W.

I was wondering on Kelly also. I did a little diving.

With his fastballs, he is throwing them harder and giving them less break. His GB% is down on each. Also, 11 of his 15 home runs have come off the fastballs.

Once he gets to 2 strikes, he is all slider which has been a great swing-and-miss pitch. But he can’t throw it for strikes.

So he has to use the “bad” fastballs to try to get two strikes. Once he gets two strikes, the slider is able to finish off the hitters.

Mike W.
7 years ago
Reply to  Jeff Zimmerman

Wow, great info Jeff, thanks for digging into that. Kelly has been on my radar with the K’s and the hope he may be able to turn it around ERA and WHiP wise. It seems instead that he could remain incredibly inconsistent at best with this tweaked arsenal of his and his inability to throw strikes consistently with his slider.

Jim Lahey
7 years ago
Reply to  Jeff Zimmerman

He can throw the ball hard and can throw some good pitches – but his game plan is weak and his control is inconsistent. So he racks up strikeouts because of his stuff. He’s seemingly up too high in the zone and get’s hurt because he’s basically all fastball/slider.. too predictable. He’s getting hammered when he’s ahead in the count… because he’s getting a lot of the plate with it.

Jeff Zimmermanmember
7 years ago
Reply to  Jeff Zimmerman

I need to get some work published, but I have found that limiting hard hit (LD data) may take a while to stabilize, if at all.

Preventing or allowing home runs is a different story.

They need to be treated differently.

7 years ago
Reply to  Jeff Zimmerman


When you say there’s little YoY correlation between HH%, could you elaborate? Specifically, I could see this making more sense if this was within a range (i.e., each pitcher had a range of HH% allowed, within which they varied significantly). It makes sense that there’s going to be a LOT of variance YoY with this stat, but OTOH, it really doesn’t make any sense to me that this would be a completely independent variable. After all, we all know that poorer pitchers give up more HH balls. I am going to allow close to 100% HH balls (assuming I get any over the plate), whereas peak Kershaw or RJ will have a much lower number. So it strikes me that this is a lot like BA or even BABIP, which is to say there’s a lot of variance but also that variance occurs within a certain range (which is controlled by the player). Thoughts?